PROJECT SUMMARY Significant racial, ethnic, and socioeconomic disparities exist in access to diagnostic and treatment services for children with autism spectrum disorder (ASD). Because earlier access to ASD services improves long-term outcomes, delayed engagement with these services can be responsible for substantial morbidity. This pattern of health service break-down ? delay in care, leading to preventable morbidity ? exists in many sectors of the US health care system. One promising solution, which has been studied extensively over the past ten years, is patient navigation. Patient navigation is a lay-delivered case management strategy designed to reduce health disparities by helping vulnerable populations overcome psychological and logistical hurdles to care. Navigation has proven effectiveness in multiple disorders such as cancer and HIV, and early data support its use as a strategy to promote timely engagement with evidence-based services among children with ASD. However, despite navigation's substantial effectiveness data, multiple studies demonstrate the attenuation of its impact, and variable success, when implemented in real-world practice. This ?research-practice? gap ? whereby effective clinical innovations fail to be adopted (or practiced with appropriate fidelity) within real-world clinical practice ? is ubiquitous in healthcare; but it is particularly problematic for low-income and minority populations and the institutions that serve them. Furthermore, despite guidance to the contrary, few clinical trials proactively collect data on the complex patient, provider, and organizational factors that impact subsequent implementation of the clinical innovations being tested. As a result of this missed opportunity, implementation strategies are often arbitrary and prone to failure. Therefore, in this K23 application, I propose to use emerging techniques in the field of dissemination and implementation science to evaluate key implementation processes of patient navigation in the context of an ongoing, NIMH-funded, multi-site randomized controlled trial of a patient navigation system designed to improve access to care for low-income children with ASD (R01MH104355, Feinberg). The goal of this work is to elucidate factors that can increase the likelihood of rapid and sustained uptake of patient navigation in diverse, real-world practice settings. My educational objectives are to gain training and experience in dissemination and implementation science through the following goals: to learn process mapping and analysis; to learn new qualitative methods; and to learn and apply a new quantitative technique - multilevel modeling. The research in this proposal builds directly on my prior work, which focused on using multidisciplinary teams to improve access to services for children with ASD and their families. I have identified an experienced mentoring team and a supportive research environment, which will ensure that I attain my immediate and long-term goals. At the end of the award, I will be position to develop a testable data-driven implementation strategy to promote the rapid dissemination and implementation of patient navigation to vulnerable children with ASD.